Acoustic telemetry residency analysis

Summary

Target folder: C:/Git/ETN_workshop_Jan2021/actel_example

Timestamp: 2021-01-25 15:38:14

Number of target tags: 60

Number of listed receivers: 17 (of which 1 had no detections)

Data time range: 2018-04-13 22:26:37 to 2018-05-25 17:46:13 (Europe/Copenhagen).

Percentage of post-release valid detections: 100%

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Study area

Arrays with the same background belong to the same section. Release sites are marked with “R.S.”. Arrays connected with an arrow indicate that the animals can only pass in one direction.

Receiver stations

Station.name	Latitude	Longitude	x	y	Array	Section	Standard.name
Station -1	56.35474	8.629019	477075.2	6245625	A0	River	St.1
Station 1	56.35672	8.603097	475474.6	6245854	A1	River	St.2
Station 2	56.36505	8.510094	469734.4	6246818	A2	River	St.3
Station 3	56.34976	8.385683	462033.4	6245178	A3	River	St.4
Station 4	56.32894	8.309133	457279.2	6242906	A4	River	St.5
Station 5	56.32576	8.306444	457109.4	6242553	A5	River	St.6
Station 6	56.32267	8.303267	456909.4	6242211	A6	River	St.7
Station 7	56.32865	8.249125	453568.3	6242912	A7	Fjord	St.8
Station 8	56.32610	8.246447	453399.6	6242630	A7	Fjord	St.9
Station 9	56.32388	8.240797	453047.5	6242387	A7	Fjord	St.10
Station 10	56.32192	8.239672	452975.5	6242169	A7	Fjord	St.11
Station 11	56.37173	8.132342	446407.4	6247792	A8	Fjord	St.12
Station 12	56.37221	8.130017	446264.5	6247847	A8	Fjord	St.13
Station 13	56.37250	8.127761	446125.6	6247881	A8	Fjord	St.14
Station 14	56.37199	8.118439	445549.1	6247831	A9	Sea	St.15
Station 15	56.37256	8.118169	445533.2	6247895	A9	Sea	St.16
Station 16	56.37200	8.117658	445500.9	6247833	A9	Sea	St.17

Deployments

Receiver	Array	Station.name	Standard.name	Start	Stop
132907	A0	Station -1	St.1	2018-03-15 12:00:00	2018-06-01 12:00:00
132908	A1	Station 1	St.2	2018-03-15 12:00:00	2018-06-01 12:00:00
132909	A7	Station 7	St.8	2018-03-15 12:00:00	2018-06-01 12:00:00
132914	A5	Station 5	St.6	2018-03-15 12:00:00	2018-06-01 12:00:00
132915	A6	Station 6	St.7	2018-03-15 12:00:00	2018-06-01 12:00:00
132916	A4	Station 4	St.5	2018-03-15 12:00:00	2018-06-01 12:00:00
132917	A3	Station 3	St.4	2018-03-15 12:00:00	2018-06-01 12:00:00
132918	A2	Station 2	St.3	2018-03-15 12:00:00	2018-06-01 12:00:00
133205	A8	Station 13	St.14	2018-03-15 12:00:00	2018-06-01 12:00:00
133206	A9	Station 16	St.17	2018-03-15 12:00:00	2018-06-01 12:00:00
133209	A8	Station 12	St.13	2018-03-15 12:00:00	2018-06-01 12:00:00
133210	A9	Station 14	St.15	2018-03-15 12:00:00	2018-06-01 12:00:00
133215	A9	Station 15	St.16	2018-03-15 12:00:00	2018-06-01 12:00:00
133220	A8	Station 11	St.12	2018-03-15 12:00:00	2018-06-01 12:00:00
133221	A7	Station 10	St.11	2018-03-15 12:00:00	2018-06-01 12:00:00
133222	A7	Station 8	St.9	2018-03-15 12:00:00	2018-06-01 12:00:00
133224	A7	Station 9	St.10	2018-03-15 12:00:00	2018-06-01 12:00:00

Release sites

Station.name	Latitude	Longitude	x	y	Array	Type	Standard.name	n.A	n.B
RS1	56.349	8.6204	476539	6244988	A1	Release	RS1	30	30

Array efficiency

Note:

More information on the differences between “Known missed events” and “Potentially missed events” can be found in the package vignettes.

The data used in this table is stored in the efficiency object.

These efficiency values are estimated using a simple step-by-step method (described in the package vignettes). In some situations, more advanced efficiency estimation methods may be required.

You can try running advEfficiency(results$efficiency) to obtain beta-drawn efficiency distributions (replace results with the name of the object where you saved the analysis).

Events recorded and missed

	A0	A1	A2	A3	A4	A5	A6	A7	A8	A9
Recorded events	0	54	54	52	54	54	52	49	46	37
Known missed events	-	0	0	2	0	0	0	1	0	-
Potentially missed events	-	0	0	0	0	0	0	0	0	-

Array efficiency

Note: These values already include any intra-array efficiency estimates that have been requested.

	A0	A1	A2	A3	A4	A5	A6	A7	A8	A9
Maximum efficiency	-	100%	100%	96.3%	100%	100%	100%	98%	100%	-
Minimum efficiency	-	100%	100%	96.3%	100%	100%	100%	98%	100%	-

Warning messages

Warning: GUI is set to 'needed' but packages 'gWidgets2', 'gWidgets2RGtk2', 'RGtk2' are not available. Please install them if you intend to run GUI.
         Disabling GUI (i.e. GUI = 'never') for the current run.
Warning: No detections were found for receiver(s) 132907.
Warning: 'speed.warning'/'speed.error' were not set, skipping speed checks.
Warning: 'inactive.warning'/'inactive.error' were not set, skipping inactivity checks.
Warning: Section movements with less than 2 detections are present for tag R64K-4503 (28/54).

User comments

R64K-4503   This is a lovely fish

Biometric graphics

Note:

The data used in this graphic is the data present in the biometrics.csv file.

Last seen

Note:

The data used in this table and graphic is stored in the last.seen object.

	Disap. in River	Disap. in Fjord	Disap. in Sea	Disap. at Release
A	0	6	20	4
B	4	9	15	2

Average time of arrival at each Array

Note:

Coloured lines on the outer circle indicate the mean value for each group and the respective ranges show the standard error of the mean. Each group’s bars sum to 100%. The number of data points in each group is presented between brackets in the legend of each pannel.

You can replicate these graphics and edit them as needed using the plotTimes() function.

The data used in these graphics is stored in the array.times object.

Time details for each section

Arrival days at each section

Note:

The data used in these graphics is stored in the section.times$arrival object.

Arrival times at each section

Note:

Coloured lines on the outer circle indicate the mean value for each group and the respective ranges show the standard error of the mean. Each group’s bars sum to 100%. The number of data points in each group is presented between brackets in the legend of each pannel.

You can replicate these graphics and edit them as needed using the plotTimes() function.

The data used in these graphics is stored in the section.times$arrival object.

Departure days at each section

Note:

The data used in these graphics is stored in the section.times$departure object.

Departure times at each section

Note:

Coloured lines on the outer circle indicate the mean value for each group and the respective ranges show the standard error of the mean. Each group’s bars sum to 100%. The number of data points in each group is presented between brackets in the legend of each pannel.

You can replicate these graphics and edit them as needed using the plotTimes() function.

The data used in these graphics is stored in the section.times$departure object.

Global residency

Note:

The data used in these graphics is stored in the global.ratios and time.positions objects.

You can replicate these graphics and edit them as needed using the plotRatios() function.

This data is also available split by group in the group.ratiosobject.

You can plot these results by group using the ‘group’ argument in plotRatios().

Absolutes

Percentages

Individual residency plots

Note:

The data used in these graphics is stored in the time.ratios object (one table per tag). More condensed information can be found in the section.movements object.

You can replicate these graphics and edit them as needed using the plotResidency() function.

Individual detection plots

Note:

You can choose to plot detections by station or by array using the detections.y.axis argument.

The detections are coloured by section. The vertical black dashed line shows the release time. The full dark-grey line shows the movement events considered valid, while the dashed dark-grey line shows the movement events considered invalid.

Manually edited tags are highlighted with yellow graphic borders.

Manually overridden tags are highlighted with red graphic borders.

The arrays have been aligned by section, following the order provided either in the spatial input or the section.order argument.

You can replicate these graphics and edit them as needed using the plotDetections() function.

You can also see the movement events of multiple tags simultaneously using the plotMoves() function.

The data used in these graphics is stored in the detections and movements objects (and respective valid counterparts).

Sensor plots

Note:

The colouring in these plots will follow that of the individual detection plots, which can be modified using detections.y.axis.

The data used for these graphics is stored in the valid.detections object.

You can replicate these graphics and edit them as needed using the plotSensors() function.

Full log

Actel R package report.
Version: 1.2.1

Target folder: C:/Git/ETN_workshop_Jan2021/actel_example
Timestamp: 2021-01-25 15:38:14
Function: residency()

M: 'report' option has been activated.
M: Importing data. This process may take a while.
M: Number of target tags: 60.
M: Matching detections with deployment periods.
M: Number of ALS: 17 (of which 1 had no detections)
Warning: No detections were found for receiver(s) 132907.
M: Data time range: 2018-04-13 22:26:37 to 2018-05-25 17:46:13 (Europe/Copenhagen).
M: File 'distances.csv' found, activating speed calculations.
M: Data successfully imported!
M: Creating movement records for the valid tags.
M: Checking movement events quality.
Warning: 'speed.warning'/'speed.error' were not set, skipping speed checks.
Warning: 'inactive.warning'/'inactive.error' were not set, skipping inactivity checks.
M: Compiling and checking section movements for the valid tags.
Warning: Section movements with less than 2 detections are present for tag R64K-4503 (28/54).
M: Filtering valid array movements.
M: Filtering valid section movements.
M: Compiling residency objects.
M: Calculating daily locations for each tag.
M: Calculating inter-array efficiency.
M: Saving results as 'actel_residency_results.RData'.
M: Producing the report.
M: Drawing individual detection graphics.
M: Drawing individual residency graphics.
M: Printing sensor values for tags with sensor data.
M: Process finished successfully.

-------------------
User comments:
-------------------
R64K-4503: This is a lovely fish
-------------------
User interventions:
-------------------
comment # on R64K-4503
This is a lovely fish
n # invalidate/expand moves in R64K-4503?
y # save results?
-------------------
Function call:
-------------------
residency(tz = 'Europe/Copenhagen', section.order = NULL, datapack = NULL, max.interval = 60, minimum.detections = 2, start.time = NULL, stop.time = NULL, speed.method = c('last to first'), speed.warning = NULL, speed.error = NULL, jump.warning = 2, jump.error = 3, inactive.warning = NULL, exclude.tags = NULL, override = NULL, report = TRUE, auto.open = TRUE, discard.orphans = FALSE, discard.first = NULL, save.detections = FALSE, section.minimum = 2, timestep = 'days', replicates = NULL, inactive.error = NULL, GUI = 'never', save.tables.locally = FALSE, print.releases = TRUE, detections.y.axis = 'auto')
-------------------

Index:

Summary Study area Stations Deployments Release sites Array efficiency Warnings Comments Biometrics Last seen Array times Section times Global residency Individual residency Individual detections Sensor data Full log